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Abstract Various techniques for remote monitoring of ships have been developed but have limitations, for example, lack of monitoring information, difficulty in remote control, etc. Recently, digital twin technology has been mentioned as a way to overcome such limitations. A digital twin is a digital replica (‘virtual twin’) of a living or non-living physical entity (‘physical twin’). When applying the digital twin concept to the ship remote operating system, the actual ship can be a physical twin, and the onshore control center can be a virtual twin. In this study, an integrated ship remote operating system is proposed to operate and control the actual ship in the remote environment. The proposed system consists of three components: physical twin, virtual twin, and digital twin framework. The physical twin represents the actual ship to be monitored and controlled. The virtual twin is a digital replica of the actual ship that can be monitored and controlled in the onshore control center. The digital twin framework (simply, framework) means a middleware for data transfer and storage between the physical and digital twins. All data from the simulator is transferred to the onshore control center through the framework. The onshore control center receives relevant data from the framework and visualizes various information for monitoring and control of the simulator. The result shows that the proposed system can be used effectively to implement various types of ship remote operating systems.

Keyword: Ship remote operating system; Digital twin
Publication Date 2019-10-16

Jisang Ha, Myung-Il Roh, Jong-Hyeok Lee, Jin-Hyeok Kim, Min-Chul Kong, Seung-Ho Ham, "Integrated Ship Remote Operating System Based on Digital Twin Technology", Proceedings of TEAM 2019, Tainan, Taiwan, pp. 106, 2019.10.14-17


  1. John-Kyu Hwang, Myung-Il Roh, Ju-Hwan Cha, "Design Modification of a Damaged Free-Fall Lifeboat for FPSO through the Free-Fall Test", Proceedings of ISOPE(International Society of Offshore and Polar Engineers) 2014, Busan, Korea, 2014.06.15-20

  2. John-Kyu Hwang, Myung-Il Roh, Ji-Hyun Hwang and Ju-Hwan Cha, Kyu-Yeul Lee, "Overview on Detailed Design and Construction of 2,000,000BBLS FPSO", Proceedings of Design & Construction of FPU(Floating Production Units) 2007, Suntec, Singapore, pp. 1-6, 2007.04.03

  3. John-Kyu Hwang, Geun-Jae Bang, Myung-Il Roh, Kyu-Yeul Lee, "Detailed Design and Construction of the Hull of an FPSO(Floating, Production, Storage, and Off-loading unit)", Proceedings of ISOPE 2009, Osaka, Japan, pp. 151-158, 2009.06.21-26

  4. Jisang Ha, Myung-Il Roh, Sung-Jun Lee, Ki-Su Kim, Seung-Min Lee, "Toward Rapid Flooding Analysis of a Ship Using Surrogate Model by Deep Learning", Proceedings of the 31st Asian-Pacific TEAM 2017, Osaka, Japan, pp. 397-400, 2017.09.25-28

  5. Jisang Ha, Myung-Il Roh, Sung-Jun Lee, Ki-Su Kim, Seung-Min Lee, "Toward Rapid Analysis Using Surrogate Model by Deep Learning and Application to Ship Flooding Analysis", Proceedings of ISCDE 2017, Ho Chi Minh, Vietnam, pp. 1-2, 2017.12.13-16

  6. Jisang Ha, Myung-Il Roh, Ki-Su Kim, Min-Chul Kong, "Integrated Method for the Arrangement Design of a Ship for Implementing Digital Twin in Design", Proceedings of PRADS 2022, Dubrovnik, Croatia, 2022.10.09-13

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    Jisang Ha, Myung-Il Roh, Jong-Hyeok Lee, Jin-Hyeok Kim, Min-Chul Kong, Seung-Ho Ham, "Integrated Ship Remote Operating System Based on Digital Twin Technology", Proceedings of TEAM 2019, Tainan, Taiwan, pp. 106, 2019.10.14-17

  8. Jisang Ha, Myung-Il Roh, Hye-Won Lee, Jong-Ho Eun, Jong-Jin Park, Hyun-Joe Kim, "A Method of the Collision Avoidance of a Ship Using Real-time AIS Data", Proceedings of ACSMO 2020, Seoul, Korea, pp. 106, 2020.11.23-25

  9. Jin-Hyeok Kim, Myung-Il Roh, In-Chang Yeo, Ki-Su Kim, Min-Jae Oh, Sejin Oh, "Estimation Model of Hydrodynamic Performance Using Hull Form Variation and Deep Learning", Proceedings of PRADS 2022, Dubrovnik, Croatia, pp.??, 2022.10.09-13

  10. Jin-Hyeok Kim, Myung-Il Roh, In-Chang Yeo, Ki-Su Kim, "Estimation of the Hydrodynamic Performance of the Parameterized Hull Forms Using Deep Learning", Proceedings of G-NAOE 2022, Changwon, Korea, 2022.11.06-10

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